4D AR Construction Progress Monitoring via Point Cloud Integration
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Solution Overview
Problem
Current methods for tracking construction progress are labor-intensive, time-consuming, and inefficient, relying on manual data collection and subjective interpretations, which hinder accurate and timely monitoring and visualization of construction site deviations from planned to actual status.
Innovation Solution
A probabilistic model for automated progress tracking and visualization that integrates Building Information Models (BIM) with three-dimensional (3D) and four-dimensional (4D) point cloud models, using Structure-from-Motion (SfM) and Multi-View Stereo (MVS) techniques to generate as-built models from unordered daily photographs, accounting for occlusions and dynamic changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated progress tracking using probabilistic models and 4D augmented reality is implemented, then monitoring accuracy and efficiency are improved, but system complexity and computational requirements increase
Solution Approach 1:
The patent creates a virtual 4D augmented reality copy of the construction site by integrating Building Information Models (BIM) with point cloud data from daily photographs. This digital replica allows automated progress tracking without physically visiting the site, improving monitoring efficiency while managing complexity through virtual representation
Solution Approach 2:
The patent uses a probabilistic model as an intermediary between raw photograph data and progress assessment. This model processes unordered daily photographs, extracts meaningful progress information, and compares it against planned construction schedules, automating the monitoring process while handling complexity through statistical processing
2Measurement precision
If manual data collection and subjective interpretation methods are used, then system complexity is reduced, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent replaces manual data collection and subjective interpretation with automated computer vision systems. Point cloud models generated from daily photographs are automatically processed and compared against BIM models to detect progress deviations, eliminating human error while managing complexity through algorithmic processing
Solution Approach 2:
The patent implements automated feedback loops where progress data from point cloud models is continuously compared against planned construction schedules. Deviations are automatically detected and visualized in 4D augmented reality, providing real-time feedback on construction status without requiring manual analysis
3Loss of information
If existing reporting methods like progress S curves and schedule bar charts are used, then ease of operation is improved, but information completeness and visualization quality deteriorate
Solution Approach 1:
The patent transitions from traditional 2D reporting methods to 4D augmented reality visualization. By adding the time dimension to 3D spatial models, the system presents construction progress in an immersive environment that simultaneously displays spatial relationships, temporal progression, and deviation information, eliminating information loss while maintaining ease of access through interactive viewing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and accurate automated monitoring of construction progress, reducing manual intervention and subjective errors, and effectively visualizing deviations in real-time, facilitating better project control and decision-making.
Implementation Method 1
using Structure-from-Motion (SfM) and Multi-View Stereo (MVS) techniques to generate as-built models from unordered daily photographs
Implementation Method 2
using Structure-from-Motion (SfM) and Multi-View Stereo (MVS) techniques to generate as-built models from unordered daily photographs
Data Source
AI summary
A method for monitoring construction progress may include storing in memory multiple unordered images obtained from photographs taken at a site; melding the multiple images to reconstruct a dense three-dimensional (3D) as-built point cloud model including merged pixels from the multiple images in 3D space of the site; rectifying and transforming the 3D as-built model to a site coordinate system existing within a 3D as-planned building information model (“as-planned model”); and overlaying the 3D as-built model with the 3D as-planned model for joint visualization thereof to display progress towards completion of a structure shown in the 3D as-planned model. The processor may further link a project schedule to the 3D as-planned model to generate a 4D chronological as-planned model that, when visualized with the 3D as-built point cloud, provides clash detection and schedule quality control during construction.