Subsurface Utility Mapping Using Surface Markings and Image Analysis
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Solution Overview
Problem
Conventional methods for mapping subsurface utility infrastructure are inadequate in precision and accuracy, often relying on outdated or incomplete data, which can lead to disruptions during excavations or maintenance.
Innovation Solution
A digital mapping system that utilizes processing circuitry to analyze digital images of a surface area, identify surface features, calculate utility locations from these features, and define zones containing subsurface utility infrastructure, incorporating techniques like computer vision and machine learning to enhance precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mapping methods are used, then the mapping process is simple and quick, but the precision and accuracy of subsurface utility location are insufficient
Solution Approach 1:
The mapping process is divided into distinct segments: image acquisition from multiple sources, surface feature identification through computer vision, utility location calculation based on feature types, and digital map generation. This segmentation allows each step to be optimized independently, improving overall precision while managing complexity through modular processing
Solution Approach 2:
The system performs preliminary actions by acquiring and processing multiple types of images and identifying surface features before actual utility location determination. This advance preparation creates a comprehensive data foundation that enhances measurement precision when calculating utility locations, reducing the need for repeated measurements and corrections
2Reliability
If conventional mapping methods are used, then the equipment and process are simple, but the accuracy and reliability of utility location data are poor
Solution Approach 1:
The system merges multiple image sources (aerial, ground-based, historical) and combines them with surface feature data and utility location calculations into a single integrated digital map. This merging of diverse data sources enhances reliability by cross-validating information and providing multiple lines of evidence for utility locations, while the integrated system manages complexity through unified processing workflows
Solution Approach 2:
The system incorporates feedback mechanisms where calculated utility locations are validated against multiple image sources and surface features. Discrepancies trigger re-evaluation and refinement of location data, improving reliability through iterative verification. The feedback loop ensures high accuracy by continuously checking calculated positions against independent data sources
3Measurement precision
If multiple image types and processing techniques are integrated, then the precision of utility location is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of multiple image types and identification of surface features before utility location calculation. This advance preparation organizes and pre-processes data in a structured manner, reducing computational burden during the actual location determination phase and minimizing processing time despite the complexity of multiple data sources
Solution Approach 2:
The processing system dynamically adjusts its operations based on data availability and quality. It prioritizes processing of most relevant image types and surface features first, adapting the processing sequence to optimize accuracy while managing time constraints. This dynamic approach allows flexible resource allocation during different stages of map generation
Data Source
AI summary
There is provided a digital map product comprising data informative of a location of a zone in a surface area including a subsurface utility infrastructure (SUI), the digital map product being derivative of a method comprising: receiving a digital image of the surface area; identifying a plurality of surface features; for each of the plurality of surface features: calculating an indication of utility location (IUL) from the respective surface feature and location, wherein the IUL is one of: a location of a point of the SUI, a location of a zone of the SUI, a location of a zone from which the SUI is absent, thereby giving rise of a plurality of IULs; and defining a location of a zone including the SUI in accordance with, at least, the plurality of IULs wherein at least one surface feature of the plurality of surface features is a public works surface marking.