Intelligent project special consultation management system and method based on multi-source data fusion
By employing multi-source data fusion and intelligent collaboration, the problems of data heterogeneity, passive business process collaboration, and outdated knowledge management in the preparation and review of multi-specialty consulting reports for large-scale engineering projects have been solved. This has enabled efficient and intelligent project consulting management, improving data processing efficiency, analysis quality, and knowledge accumulation.
Patent Information
- Application Number
- CN202610406755.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-31
- Publication Date
- 2026-05-29
AI Technical Summary
In the early planning and approval stages of large-scale engineering projects, the preparation and review of multiple specialized consulting reports suffer from problems such as data heterogeneity and semantic barriers, passive collaboration of business processes, reliance on personal experience for analysis and decision-making, and outdated report output and knowledge management methods. These issues lead to inefficiency, inconsistent quality, loss of knowledge assets, and duplication of work.
By adopting a multi-source data fusion and intelligent collaboration approach, an intelligent project-specific consulting management system is constructed through a unified data platform, multi-source data semantic fusion, adaptive workflow configuration, multi-model coupled simulation, intelligent conflict detection and causal reasoning, and immersive report generation. This system enables automated association and structuring of multi-source data, dynamic configuration of task resources, real-time collaborative simulation across models, in-depth detection and causal analysis of cross-professional conflicts, immersive visualization of reports, and structured management of knowledge.
It improved the efficiency of data preprocessing and the accuracy of compliance review, enhanced the overall efficiency and resilience of task scheduling, ensured the internal logical consistency of analysis results, enhanced the efficiency and depth of cross-disciplinary problem solving, improved the report review experience and knowledge management methods, and realized the continuous evolution of the system's intelligence level.