Keywords

Extended Reality, Mixed Reality, Retrofitting, BIM, Architecture, Robotics

Abstract

Rapidly changing population dynamics and increased energy needs have reduced demand for building renovation in favor of more wasteful complete demolition and reconstruction. This dissertation aims to enhance the accessibility and ease of use of challenging retrofitting methodologies to mitigate adverse effects of urbanization, increasing resource use, and aging building stock within the United States. Retrofitting is a process focused on upgrading a component or feature of a structure that was not initially constructed or manufactured, and it is often done to modernize, restore, or repurpose a structure. These renovations are difficult and costly to plan and implement, frequently contributing to eschewing them in favor of complete reconstruction. This research proposes a solution: integrating Extended Reality (XR) technology and Building Information Modeling (BIM) data into the retrofitting workflow. Individually and together, these technologies have been applied to construction work with great success, although this area has previously been predominantly confined to new construction. We present this concept applied to three retrofitting subprocesses: design, implementation training, and model building. For each component, a human-subject study evaluates the system’s effectiveness in improving the efficiency and accessibility of this technology in this new context. We found that when applied to design review, technological limitations of existing XR systems may limit their ability to separate from conventional means, but increasing emphasis on eye movement in the future system design should be prioritized depending on environmental factors. In implementation training, these systems can effectively improve the identification of relevant building components while reducing physical and cognitive demands. Investigation into augmenting human-robot collaboration is still ongoing, but early results indicate great potential in improving control and ease of use when performing tasks later needed to create building models for guiding retrofitting projects. This dissertation provides a foundation for XR-BIM technology applied to retrofitting and, with it, a positive outlook and recommendations for related future work.

Completion Date

2024

Semester

Summer

Committee Chair

Kider, Joseph

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

School of Modeling, Simulation, and Training

Degree Program

Modeling & Simulation

Format

application/pdf

Identifier

DP0028514

URL

https://purls.library.ucf.edu/go/DP0028514

Language

English

Release Date

8-15-2024

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Campus Location

Orlando (Main) Campus

Accessibility Status

Meets minimum standards for ETDs/HUTs

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