An operation and maintenance strategy of intelligent building information model data based on cloud computing

Abstract

The operation and maintenance (O&M) of intelligent building information model (IBIM), as an important aspect of modern building informatization, plays a critical role in the construction of smart cities and the renovation of modern buildings. Due to the complex structure and sheer size of IBIM data, the O&M system of IBIM faces a huge workload and a high cost. Based on cloud computing, this paper proposes an O&M strategy for IBIM data, which meets the needs for stable management of massive data, enables three-dimensional (3D) collaborative visualization of building information model (BIM), improves the efficiency of data storage, scheduling, and O&M. Firstly, the basic structure of IBIM data was standardized according to The Industry Foundation Classes (IFC) (ISO 16739-1:2018). Then, the features were sampled from the standardized IBIM cloud data. After that, the storage data were subject to routing, coding, matching feature compression, and adaptive attribute clustering. On this basis, an optimization model was established for the storage structure of IBIM cloud data. Finally, a batch feature extraction method was designed for 3D structure distribution of job-based 3D cloud storage model. The proposed strategy was proved effective through experiments. The research results provide a reference for applying 3D cloud storage model in other fields.