3D BIM Progress Tracking with Machine-Learned Object Detection
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Solution Overview
Problem
There is a need for improved methods to track and monitor the progress of construction sites, particularly in buildings, to ensure accurate identification and documentation of construction work, including the presence or absence of specific objects and their installation status.
Innovation Solution
A method utilizing a 3D Building Information Modeling (BIM) model combined with a walk-through recording camera and machine learning, where captured images are processed to identify objects within the 3D model, allowing for detailed progress tracking and generation of reports tailored to specific contractors or craftsmen.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If 2D floorplans are used for training machine learning models to identify construction objects, then the training process can be simplified, but the identification accuracy and detail of object characteristics are reduced
Solution Approach 1:
The patent transitions from 2D floorplan representations to 3D BIM models for object identification. The 3D models provide comprehensive geometric information, material properties, and spatial relationships that significantly improve the machine learning model's ability to accurately identify construction objects, their characteristics, and installation status while maintaining automated processing capabilities
2Loss of information
If manual inspection methods are used to track construction progress, then detailed documentation can be achieved, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection processes with an automated system combining mobile imaging devices, 3D BIM models, and machine learning algorithms. The system automatically captures images at construction sites, compares them against BIM model expectations, identifies present/absent objects, and generates progress reports without manual intervention, thereby maintaining detailed documentation while dramatically improving productivity
Solution Approach 2:
The system enables self-service progress tracking where the construction site documentation process becomes autonomous. The mobile device automatically captures images, the machine learning model independently identifies objects and their status, and the system autonomously generates comprehensive progress reports comparing actual site conditions with BIM model expectations, eliminating the need for manual inspection labor
3Loss of information
If comprehensive BIM models with all construction details are maintained, then complete project information is available, but data management complexity and processing requirements increase
Solution Approach 1:
The patent extracts and utilizes only the necessary portions of comprehensive BIM models for progress tracking purposes. The system selectively retrieves geometric information, object properties, and spatial relationships from the full BIM model that are relevant to comparing against captured images, thereby maintaining access to complete project information while reducing data management complexity by processing only essential subsets
Solution Approach 2:
The patent creates a multi-functional system where the 3D BIM model serves multiple purposes: it provides the baseline for progress tracking, defines expected object locations and characteristics, enables automated comparison with captured images, and generates progress reports. This universal approach consolidates multiple data management functions into a single integrated system, reducing overall complexity while maintaining information completeness
Data Source
AI summary
Methods for tracking construction site progress, such as for a site that includes a building based on 3D digital representation. Building information modeling (BIM) may provide a digital representation of the physical and functional characteristics of a place, such as a site with a building, the building optionally based on 3D digital representation.