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This paper presents new metrics and methods for evaluating the quality of reality capture plans—commonly used to operate camera‐mounted unmanned aerial vehicles (UAVs) or ground rovers—for construction progress monitoring and inspection of as‐is conditions. Using 4D building information model (BIM) or 3D reality model as a priori, these metrics provide feedback on the quality of a plan (within a few minutes), accounting for resolution, visibility, accuracy, completeness of the capture, and satisfying battery capacity and line‐of‐sight requirements. A cloud‐based system is introduced to create and optimize UAV/rover missions in the context of prior model. Results from real‐world construction data sets demonstrate that the proposed metrics offer actionable insights into the accuracy and completeness of reality capture plans. Additionally, a capture plan—with a combination of canonical and noncanonical camera views—that satisfies the introduced metrics is statistically correlated with the quality of reconstructed reality. These metrics can improve computer‐vision progress monitoring and inspection methods that rely on the construction site's appearance and geometry. [ABSTRACT FROM AUTHOR]

The three-dimensional mapping of the built environment is of particular importance for engineering applications such as monitoring work-in-progress and energy performance simulation. The state-of-the-art methods for fitting primitives, non-uniform B-Spline surface (NURBS) and solid geometry to point clouds still fail to account for all the topological variations or struggle with mapping of physical space to parameter space given unordered, incomplete, and noisy point clouds. Assuming an input of points that can be described by a single non-self-intersecting NURBS, this article presents a new method that leverages segmented point clouds and outputs NURBS surfaces. It starts by successively fitting uniform B-Spline curves in two-dimensional as planar cross-sectional cuts on each surface. An intermediate B-Spline surface is then computed by globally optimizing and lofting over the cross-sections. This surface is used to parameterize the points and perform final refinement to a NURBS. For cylindrical segments such as pipes, a new supervised method is also introduced to string the fitted segments, identify connection types, standardize the connections, and then refine them using NURBS optimization. Experimental results show the applicability of the proposed methods for as-built modeling purposes. [ABSTRACT FROM AUTHOR]

An inexpensive and robust 3D localization system for tracking the position of a user in GPS- or WLAN-denied environments offers significant potential for improving decision-making tasks for civil and infrastructure engineering applications. To this end, an infrastructure-free approach for 3D event localization on commodity smartphones is presented. In the proposed method, the position of the user is continuously tracked based on the smartphone sensory data (the Forward approach) until the user reaches a certain event. Here, an event location refers to the 3D location of a user conducting value-added activities such as tasks involved in emergency response and field reporting of operational issues. Once an event is observed, the motion trajectory of the user is backtracked from the postevent landmark to reestimate the location of the event (the Backward approach). By integrating probability distributions of the Forward and Backward approaches together, the proposed method derives the most-likely location of the event. To validate the proposed approach, seven case studies are conducted in a multistory parking garage. The experimental results show that the probabilistic integration of the localization results from the Forward and Backward dead reckonings can produce more accurate 3D localization results when compared to a single best estimate from a one-way dead reckoning process. Lessons learned from several real-world case studies and open research challenges in improving localization accuracy are discussed in detail. [ABSTRACT FROM AUTHOR]