Green building engineering cost collaborative management system oriented to information processing and storage support service

By constructing a multi-layered collaborative architecture, a unified semantic framework for the correlation and calculation of physical data, building information models, and unstructured contract texts in green building projects has been realized. This solves the problem of the lack of unified data anchoring in cost management, improves the accuracy of cost accounting and storage response efficiency, and enables the computable transmission and early warning of cost fluctuations.

CN122928243APending Publication Date: 2026-10-16JIANGXI WANBANG CONSTR PROJECT MANAGEMENT CO LTD
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Patent Information

Application Number
CN202610930775.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-06-26
Publication Date
2026-10-16

AI Technical Summary

Technical Problem

In the cost management of green building projects, there is a lack of a unified semantic anchoring framework for physical sensing data, building information model data and unstructured contract texts. The storage scheduling logic is disconnected from the cost business value, and the cost transmission due to material price fluctuations lacks mathematical modeling based on physical topology.

Method used

A collaborative architecture consisting of a physical perception layer, a semantic fusion processing layer, a distributed storage support layer, and a cost collaborative application layer is constructed. Through sliding window anomaly detection, bidirectional temporal neural networks, graph neural networks, multi-factor heat decay functions, and multi-objective optimization models, a unified semantic framework for data association calculation and computable transmission of cost fluctuations are achieved.

Benefits of technology

It has improved the accuracy and consistency of cost accounting, realized the transformation of cost management from post-event statistics to pre-event topology early warning, enhanced storage response efficiency and system robustness, and improved the sensitivity and pertinence of risk warning.

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Abstract

The present application belongs to the technical field of construction engineering cost collaborative management, and relates to a green building engineering cost collaborative management system facing information processing and storage support services. The present application comprises: a physical perception layer which collects environmental parameters and material data and completes cleaning and filling; a semantic fusion processing layer which analyzes building information model files to construct component topology graphs, extracts contract text semantic features by using a deep learning network, generates cross-modal fusion node features through a gated attention fusion mechanism, calculates and outputs component-level cost deviation risk indexes by using a graph neural network, and tracks and conducts paths; a distributed storage support layer which implements three-level storage migration according to a multi-factor heat decay function and processes write conflicts through a multi-version concurrency control mechanism; and a cost collaborative application layer which executes multi-objective optimization with green constraints and triggers deviation early warning. The present application improves the accuracy, response speed and system consistency of green building engineering cost collaborative management.
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