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Traditional construction projects are characterized by large scale, long duration, and multiple stakeholders, leading to issues such as inefficient management and low operational efficiency. Under the national digital transformation strategy, the construction industry must embrace digital transformation. By integrating artificial intelligence (AI), Internet of Things (IoT), and geographic information system (GIS) technologies, this study develops a command and decision-making system tailored for construction project management. The platform employs multidimensional and multilevel analysis through intelligent algorithms to enable data-driven decision-making. It achieves integrated control over key construction elements such as personnel, machinery, materials, methods, environment, quality, safety, and progress, while facilitating precise supervision and instruction delivery to project teams. Pilot applications validate the platform’s effectiveness, offering valuable insights for digital transformation in similar projects.

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Research and Development of a BIM+IoT--Based Digital Command and Decision Platform for Construction Engineering

  • 章节

  • 发表日期：

    2026年

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  • Junyi Li,
  • Xiaodan Ma,
  • Hang Yu,
  • Yansong Wang,
  • Xuejuan Dou,
  • Pengzhou Wang,
  • Yang Wang

摘要

Traditional construction projects are characterized by large scale, long duration, and multiple stakeholders, leading to issues such as inefficient management and low operational efficiency. Under the national digital transformation strategy, the construction industry must embrace digital transformation. By integrating artificial intelligence (AI), Internet of Things (IoT), and geographic information system (GIS) technologies, this study develops a command and decision-making system tailored for construction project management. The platform employs multidimensional and multilevel analysis through intelligent algorithms to enable data-driven decision-making. It achieves integrated control over key construction elements such as personnel, machinery, materials, methods, environment, quality, safety, and progress, while facilitating precise supervision and instruction delivery to project teams. Pilot applications validate the platform’s effectiveness, offering valuable insights for digital transformation in similar projects.