Digital As-Built Material Location Estimation From Load Tickets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing digital as-built databases often lack precise location information about construction materials, leading to inaccuracies and inefficiencies in project management, as load tickets typically do not provide details on material deposition or pickup locations, and image-based data is insufficient for detailed analysis.
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 and rollers, to infer and accurately record material locations, using filters and historical data to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If load tickets are used to track construction materials, then material accounting is achieved, but location information is lost
Solution Approach 1:
The system merges data from multiple sources: load tickets (material quantity and chain of custody), construction equipment operational data (GPS locations and timestamps), and project data. By combining these previously separate data streams, the system creates a unified digital as-built record that contains both material accounting information and precise location data that neither source could provide alone.
Solution Approach 2:
The system uses an intermediary matching process that connects load tickets to equipment operational data through temporal and spatial correlation. The processor acts as a mediator, matching materials to locations by comparing timestamps and geographic coordinates, thereby recovering location information that was absent from the original load tickets.
2Reliability
If image data is used for as-built documentation, then visual record is created, but detailed analysis capability is reduced
Solution Approach 1:
The system replaces image-based documentation with a data-driven digital record. Instead of relying on visual images that are difficult to search and analyze, the system uses structured data from load tickets and equipment sensors that can be easily queried, filtered, and analyzed. This substitution transforms unstructured visual information into structured, analyzable data while maintaining documentation reliability.
Solution Approach 2:
The system transitions from two-dimensional image data to multi-dimensional structured data that includes spatial coordinates, timestamps, material types, and equipment identifiers. This dimensional expansion enables sophisticated querying and analysis capabilities that are impossible with traditional image-based documentation.
3Loss of information
If manual as-built database creation is used, then comprehensive records can be compiled, but time and resource consumption increase
Solution Approach 1:
The system implements self-service by automatically collecting, processing, and organizing data from multiple sources without requiring manual intervention. Load tickets, equipment operational data, and project information are automatically ingested, matched, and compiled into the digital as-built database, eliminating the need for manual record-keeping while maintaining completeness.
Solution Approach 2:
The system performs preliminary data collection and organization during the construction process itself. Rather than compiling records after project completion, the system continuously gathers and processes data as construction activities occur, so that the digital as-built database is already populated and organized when needed, dramatically reducing creation time.
4Loss of information
If plan data is used for as-built documentation, then design information is captured, but actual construction deviations are lost
Solution Approach 1:
The system transitions from static plan data to dynamic, real-time construction data. By continuously collecting operational data from equipment during construction activities, the system captures the actual state of construction as it evolves, enabling precise tracking of deviations from original plans while preserving the design information for comparison.
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.