Technology-Driven Development and Application of Engineering Cost Databases

This paper systematically explores the development and application of engineering cost databases driven by technology. Confronting persistent challenges in traditional cost management, such as data fragmentation, over-reliance on standardized quotas, and inefficiency. The integration of technologies: big data, artificial intelligence (AI), cloud computing, blockchain, the Internet of Things (IoT), and Building Information Modeling (BIM) provides robust momentum for database construction. Specifically, it elaborates on key technological pathways for building such databases, encompassing: the integration and standardization of multi-source heterogeneous data; the utilization of data lakes, Natural Language Processing (NLP), knowledge graphs, and intelligent analytical prediction models based on algorithms like Random Forest and Long Short-Term Memory (LSTM); dynamic update mechanisms; and integration with cloud platforms and real-time data acquisition. Practical case studies, including Shandong Province's initiatives, the "Smart Cost" system in Chancheng District, Guangzhou, the material price database of Rizhao Municipal Housing and Urban-Rural Development Bureau, and Yema Technology's AI database, demonstrate the efficacy of these technological applications. Finally, the paper anticipates the future trajectory of engineering cost databases towards increasing intelligence, emphasizing their pivotal role in supporting intelligent construction within international projects and achieving objectives related to engineering intelligence and cost datafication. It posits that such databases will become the core engine driving the construction industry's transformation towards greater refinement, intelligence, and high-quality development.