Fernanda Leite

TL;DR: In this article, the authors evaluate the modeling effort associated with generating building information modeling (BIM) at different levels of detail and the impact of LoD in a project in supporting mechanical, electrical and plumbing (MEP) design coordination.

TL;DR: Results show that this technology in its present state is not suitable for modeling infrastructure projects, however technological developments can enable this to be an efficient way to extract measurements of inaccessible objects for progress monitoring purposes and the models can also be stored for future dimension takeoffs for decision making and asset management purposes.

TL;DR: In this paper, the authors presented an approach towards assessing building performance simulation results to actual measurements, using artificial neural networks (ANN) for predicting building energy performance, which showed a good fitness with the mathematical model with a mean absolute error of 0.9%.

TL;DR: The objective of this paper is to identify and investigate grand challenges in VIMS for the construction industry, to assist the academic and industry communities in establishing a future research agenda to solve VIMs challenges.

TL;DR: The experimental results confirmed the viability of using synthetic point clouds generated from building information models in combination with small datasets of real point clouds, and opened up the possibility of developing a segmentation model for building interiors that can be applied to as-built modeling of buildings that contain unseen indoor structures.