The Construction Site Management of Concrete Prefabricated Buildings by ISM-ANP Network Structure Model and BIM under Big Data Text Mining

In the construction industry, prefabricated buildings have developed rapidly in recent years due to their various excellent properties. To expand the application of big data text mining and Building Information Model (BIM) in prefabricated building construction, with concrete as a form of expression, the construction management of concrete prefabricated buildings is discussed. Based on the Interpretative Structural Model (ISM) and Analytic Network Process (ANP), the importance of the safety factors on the construction sites of concrete prefabricated buildings are assessed. Based on BIM, an optimized construction management platform for concrete prefabricated buildings is built, whose realization effects are characterized. The results show that prefabricated buildings have developed rapidly from 2017 to 2019. Compared with traditional buildings, they can significantly reduce the waste of resources and energy, and the savings of water resource utilization can reach 80%. Among the various safety impact elements, construction management has the greatest impact on construction safety, and the corresponding weight value is 0.3653. The corresponding weight of construction personnel is 0.2835, the corresponding weight of construction objects is 0.1629, the corresponding weight of construction technology is 0.1436, and the corresponding weight of construction environment is 0.0448. This building construction management platform is able to control the construction progress in real-time and avoid the occurrence of construction safety accidents:Me final layout of the construction site shows a good effect, and the deviation between the actual construction schedule and the expected construction schedule is small, which is of great significance for the smooth development of concrete prefabricated buildings. This is a catalyst for the future development of concrete prefabricated buildings and the application of big data technology.