Multi-Modality Temporal Fusion for Construction Progress
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Solution Overview
Problem
Current methods for determining engineering progress at construction sites based on image information are inaccurate and inflexible, lacking the ability to effectively utilize multi-modality information.
Innovation Solution
An engineering progress determination method and apparatus that employs multi-modality temporal information fusion, acquiring and processing current and historical data from various sources (like construction site images, personnel composition, and building material warehousing) to extract modality-specific temporal features, which are then fused using a dimension decoupling-based approach to accurately assess project progress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If image information is used to determine engineering progress, then the method is simple to implement, but the accuracy and flexibility are poor
Solution Approach 1:
The patent combines multiple data modalities (image information, personnel composition data, building material warehousing data) into a unified multi-modality fusion framework. This merging of diverse data sources allows the system to maintain implementation simplicity while significantly improving accuracy by leveraging complementary information from different modalities to determine engineering progress.
2Measurement precision
If multi-modality information is integrated, then the accuracy of engineering progress determination is improved, but the system complexity increases
Solution Approach 1:
The patent segments the multi-modality fusion process into distinct modules: modality-specific temporal feature extraction modules for each data type, a dimension decoupling mechanism, and a fusion module. This segmentation allows complex multi-modality integration to be broken down into manageable, independent components that can be processed and combined systematically, reducing overall system complexity while maintaining high accuracy.
3Adaptability or versatility
If temporal features are extracted from multi-modality data, then the flexibility and accuracy are improved, but the computation complexity increases
Solution Approach 1:
The patent introduces temporal dimensionality to multi-modality data by extracting temporal features that capture evolution patterns across different modalities. This dimensional transformation enables the system to analyze how image, personnel, and material data change over time, providing flexible progress determination while managing computation complexity through structured temporal feature extraction rather than exhaustive multi-dimensional analysis.
4Device complexity
If traditional image-based methods are used, then the system is simpler, but it cannot effectively utilize multi-modality information
Solution Approach 1:
The patent creates a universal multi-modality fusion framework that can process and integrate multiple types of data (images, personnel composition, building material warehousing) within a single unified system. This universal approach allows the system to effectively utilize information from all modalities simultaneously, preventing information loss while maintaining system coherence through a common fusion architecture.
Data Source
AI summary
An engineering progress determination method based on a multi-modality temporal information fusion includes: acquiring current engineering progress information of multiple modalities and corresponding historical engineering progress information for current engineering progress information of each modality; subsequently, extracting modality-specific temporal features from both current engineering progress information and historical engineering progress information; these modality-specific temporal features are then fed into a dimension decoupling-based multi-modality fusion module, resulting in fused multi-modality temporal information; and the current engineering progress is then determined based on this fused information.