Digital As-Built Database Population from Load Tickets and Machine Data
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Solution Overview
Problem
Existing digital as-built databases often lack precise location information about construction materials, leading to inaccuracies and inefficiencies in project management, maintenance, and compliance, as they typically rely on incomplete load tickets and image-based data.
Innovation Solution
An automatic system that populates a digital as-built database by correlating electronic load tickets with operational data from construction equipment, such as pavers, to infer and accurately record material delivery locations, using filters and historical data to enhance precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital as-built databases rely on traditional load tickets and image-based data, then data collection is simple, but location information precision is insufficient
Solution Approach 1:
The patent combines multiple data sources (load tickets, thermal images, GPS coordinates, construction equipment operational data) into a unified digital as-built database system. By merging these previously separate data streams, the system achieves precise material location tracking without requiring a complete system overhaul, thus improving measurement precision while limiting complexity increase.
Solution Approach 2:
The patent introduces an intermediary processing layer that correlates data from different sources (load tickets with thermal images, GPS data with equipment operational data) to derive accurate material locations. This intermediary layer acts as a mediator that transforms incomplete individual data sources into precise location information without directly increasing field collection complexity.
2Reliability
If digital as-built databases use detailed material location data, then project management accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent performs preliminary correlation and processing of data during the construction phase itself, rather than attempting to process all raw data afterward. By pre-establishing the relationship between load tickets, thermal images, and GPS coordinates as materials are placed, the system achieves high project management accuracy while avoiding the complexity of post-hoc processing of massive raw datasets.
3Productivity
If digital as-built databases are populated manually with complete information, then data accuracy is high, but time consumption increases
Solution Approach 1:
The patent implements a self-service automated system where the digital as-built database populates itself by automatically correlating data from load tickets, thermal images, and GPS coordinates. The system performs self-correlation and self-validation of material locations without manual intervention, achieving both high data accuracy and rapid population speed simultaneously.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously validates and correlates incoming data against existing database records. This feedback loop automatically corrects discrepancies and confirms material locations, ensuring high data accuracy while maintaining rapid automated population speeds without manual verification.
Data Source
AI summary
Systems and methods automatically populate a digital as-built database from information about loads of construction materials delivered to construction projects, even if load tickets for the construction materials lack data indicating locations to or from which respective the loads were hauled. Construction machine sensor data is automatically collected from on-project construction equipment and matched with a filtered set of digital material load tickets collected from suppliers who provided the construction materials. These matches are used to estimate locations where the delivered construction materials are ultimately placed in the construction projects, and these locations are added to the as-built database, in association with their respective load tickets. In some cases, inferences are automatically drawn to automatically smooth or adjust location information in the machine sensor data, for example based on load ticket data, historical equipment or inspection information, and/or other data sources. These systems can generate a digital as-built on demand.