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Uncertainties are modeled as probability bands (e.g. spatial bands with certain probabilities of enclosing the "true" location of utilities).
Location of utilities for underground construction represents an inexact and uncertain process in which errors can be costly and even catastrophic.
This research modeled uncertainties of buried utilities data as probability bands, described by pairs of band size and the probability of the 3D space constructed by "buffering" at the band size to enclose the "true" location of utilities.
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However, where the location of utility networks coincides sufficiently with the highway routes, the situation becomes more favourable to the utility tunnel concept.
Multi-model inference techniques [38] can be used to achieve consensus about the functional form of attribute-pressure relationships, the precise location of utility thresholds, and indicator-pressure relationships.
Here are some things to keep in mind: Location of utility lines.
This information can be usefully exploited during excavation by displaying not only the expected locations of utilities to an operator, but also the degree of uncertainty (or "buffer") associated with the expected locations in the form of a "halo".
The illustration may also include buildings, repairs, modifications or structural improvements on the property as well as locations of utilities, including water pipes and other plumbing, electrical, cable and/or telephone lines, gas lines, and utility poles.
When the locations of utility lines are collected directly such as in GPR, the 3D Probability G-band can be simplified into 3D Probability Bands that can be derived via the 3D buffering approach.
Consequently, not only the 3D shapes and locations of utility lines and vertices, but also the associated uncertainties could be visualized, as 3D probability bands in a geospatial AR environment.
The facilities management utilizes the stored tag location of the utilities in order for facilities management, including real-time feed of surround tagged objects, automated scheduling for maintenance, automated summary and reporting and indoor localization (Costin et al. 2012a).
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